MD-TASK

MD-TASK analyzes molecular dynamics (MD) trajectories using graph-theory and network-analysis methods to characterize correlated motions, interaction networks, and perturbation-sensitive regions in biological macromolecules.

Key Features:

• Graph theory and network analysis: Applies graph-theory and network-analysis approaches to MD trajectories to represent and analyze interactions within biomolecular systems.
• Perturbation Response Scanning (PRS): Implements Perturbation Response Scanning (PRS) to identify regions of macromolecules that are sensitive to perturbations.
• Dynamic Cross-Correlation Analysis: Assesses correlated motions between different parts of a molecule over time using dynamic cross-correlation analysis.

Scientific Applications:

• Structural bioinformatics: Supports detailed examination of macromolecular dynamics in structural bioinformatics studies.
• Protein folding: Aids analysis of conformational transitions in protein folding studies using MD trajectories.
• Enzyme mechanisms: Enables investigation of enzyme mechanisms by mapping dynamic interactions and perturbation-sensitive regions.
• Drug–receptor interactions: Assists characterization of drug–receptor interactions by identifying correlated motions and perturbation-sensitive sites.
• Other molecular dynamics studies: Applicable to other dynamic processes at the molecular level examined by MD simulations.

Methodology:

Implemented in Python.